Social media driven information interface

ABSTRACT

One or more techniques and/or systems are provided for populating an information interface based upon social media data. For example, users may post, share, and/or discuss various information through social media sources. Accordingly, social media data may be obtained from such social media sources. The social media data may be grouped into sets of social media data based upon temporal information. Within the sets of social media data, social media entries may be clustered into topic clusters (e.g., a royal wedding topic cluster, a plane crash topic cluster, etc.). Event summaries may be generated for respective topic clusters. The event summaries may be used to populate timeslots of an information interface, such as a calendar or timeline, to create annotated timeslots. In this way, the information interface may provide users with an interactive view of events over a time period, such as a year-in-review, based upon social media data.

CROSS REFERENCE TO RELATED APPLICATION

This application is a continuation of, and claims priority from, U.S.patent application Ser. No. 14/026,864—now U.S. Pat. No. 9,299,113—filedSep. 13, 2013 and entitled “Social Media Driven Information Interface”,the entire specification of which is hereby incorporated by reference.

BACKGROUND

Many users post and share information through various social networkingservices. In an example, a user may use a mobile device to capture asoccer championship game photo of a player scoring a winning goal. Theuser may upload the soccer championship game photo to an image sharingservice for other users to view, comment on, share, and/or the like. Theuser may tag the soccer championship game photo with a hashtag, such as#championshipgoal, which may facilitate discovery of the championshipgame photo by other users performing an image search. In anotherexample, multiple users of a microblog discussion service may engage ina microblog discussion regarding a recent political debate. In this way,users may share information through image sharing services, microblogdiscussion services, social network profiles, and/or a variety of othersocial networking services.

SUMMARY

This summary is provided to introduce a selection of concepts in asimplified form that are further described below in the detaileddescription. This summary is not intended to identify key factors oressential features of the claimed subject matter, nor is it intended tobe used to limit the scope of the claimed subject matter.

Among other things, one or more systems and/or techniques for populatingan information interface based upon social media data are providedherein. Users may share, discuss, and/or discover information relatingto entities (e.g., a soccer player, a new restaurant chain, a city, anew car, etc.) and/or events (e.g., a hurricane, birth of a royal baby,a tennis championship match, etc.) associated with a wide variety oftopics through social media services, such as a photo sharing service, asocial network, a microblog service, a search engine service, etc. Suchsocial media data may be obtained from one or more social media sources.

In an embodiment, the social media data may be grouped into sets ofsocial media data based upon temporal information. For example, a firstset of social media data may be identified from the social media databased upon the first set of social media data corresponding to a firsttime range (e.g., social network posts, shared images, microblogdiscussions, and/or other social media entries corresponding to aparticular day). In this way, the sets of social media data maycorrespond to social media entries occurring within particular timeranges, such as days of the year.

Topic clusters may be identified from the sets of social media data(e.g., social media entries within respective sets of social media datamay be clustered into topic clusters). In an example, a first topiccluster may be identified from the first set of social media data. Thefirst topic cluster may comprise one or more social media entries havingtopics that are similar above a topic clustering threshold. For example,the first topic cluster may comprise social media entries pertaining toa soccer game occurring on Sep. 12, 2013, a second topic cluster maycomprise social media entries pertaining to a large corporation mergeroccurring on Sep. 12, 2013, a third topic cluster may comprise socialmedia entries pertaining to a plane crash on Sep. 13, 2013, a fourthtopic cluster may comprise social media entries pertaining to peacetreaty on Sep. 13, 2013, etc.

In an embodiment, the social media data may be grouped into topicclusters (e.g., without initially being grouped based upon temporalinformation). For example, a first topic cluster may be identifiedhaving one or more social media entries having a first topic similarityabove a first topic clustering threshold, a second topic cluster may beidentified having one or more social media entries having a second topicsimilarity above a second topic clustering threshold, etc. After thesocial media data is grouped or clustered into topic clusters, one ormore temporal groupings of social media entries within a topic clustermay be identified. For example, a sports topic cluster (e.g., a firsttopic cluster) may be identified from the social media data (e.g., notbased upon temporal information). The sports topic cluster may comprisea wide variety of sports related social media entries. A first temporalgrouping of social media entries corresponding to a first time range maybe identified from the sports topic cluster, a second temporal groupingof social media entries corresponding to a second time range may beidentified from the sports topic cluster, etc. For example, a firsttemporal grouping of social media entries derived from the sports topiccluster may comprise one or more social media entries pertaining to theOlympics, where the one or more social media entries within the firsttemporal grouping span a time range (e.g., several days) during whichthe Olympics occur. It will be appreciated that grouping social mediadata into topic clusters and then identifying a temporal grouping ofsocial media entries within a topic cluster may facilitate or simplifyfinding events that span a relatively long time span. In this way, auser may not have to peruse multiple time spans (e.g., 1 day, 2 days,etc.) to determine if two topic clusters (e.g., in neighboring days)pertain to the same event, topic, etc.

It will be appreciated that the examples provided herein are not meantto be limiting (e.g., temporal groupings are not limited to granularityof a day, days, 24 hrs., etc.). For example, social media entries may beclustered into topic clusters and/or grouped into temporal groupingscorresponding to any granularity of time ranges, such as weeks, months,or any arbitrary time period. In an example, a first temporal groupingof social media entries within a Sports topic cluster may correspond toa MLB baseball season and thus may span a time range of about 8 months,whereas a second grouping of social media entries within the Sportstopic cluster may correspond to MLB baseball playoffs and thus may spana time range of about 2 months.

Respective event summaries may be generated for different topic clustersand/or for different temporal groupings of social media entries within atopic cluster. For example, the soccer game social media entries withinthe first topic cluster may be evaluated to generate a soccer eventsummary describing the soccer game on Sep. 12, 2013 (e.g., the soccerevent summary may comprise an image, a short description of the soccergame, a social network message, a hashtag, a description of the teamsthat played the soccer game, and/or a variety of other information thatmay correspond to soccer game social media entries having a rankingabove a popularity threshold, such as a relatively high number ofshares, likes, views, etc.). In an example, one or more event summariesmay be annotated with a category, such as sports, entertainment, etc.Thus, a user may filter event summaries for events corresponding to aparticular category (e.g., of interest to the user). In this way, eventsummaries may be created for time ranges based upon topic clusters(e.g., the soccer event summary and a corporation merger event summarymay be associated with a Sep. 12, 2013 time range, a plane crash eventsummary and a peace treaty event summary may be associated with the Sep.13, 2013 time range, etc.). In this way, timeslots (e.g., timeslotsrepresenting days, weeks, months, etc.) of an information interface,such as a calendar or timeline, may be populated with event summaries.The information interface may provide a historical, a current, and/or afuture summary of events identified from social media data (e.g., ayear-in-review, a future event predicted based upon a recurring eventsuch as the Olympics; etc.). It may be appreciated that the informationinterface may be provided through various types of interfaces, such as acalendar app, a search results page, as a social network interface, atimeline, a carousel, and/or any other (e.g., interactive) interface.

To the accomplishment of the foregoing and related ends, the followingdescription and annexed drawings set forth certain illustrative aspectsand implementations. These are indicative of but a few of the variousways in which one or more aspects may be employed. Other aspects,advantages, and novel features of the disclosure will become apparentfrom the following detailed description when considered in conjunctionwith the annexed drawings.

DESCRIPTION OF THE DRAWINGS

FIG. 1 is a flow diagram illustrating an exemplary method of populatingan information interface based upon social media data.

FIG. 2 is a component block diagram illustrating an exemplary system forobtaining social media data.

FIG. 3 is a component block diagram illustrating an exemplary system foridentifying sets of social media data.

FIG. 4 is a component block diagram illustrating an exemplary system foridentifying topic clusters for sets of social media data.

FIG. 5 is a component block diagram illustrating an exemplary system foridentifying a relationship between entities associated with social mediaentries.

FIG. 6A is a component block diagram illustrating an exemplary systemfor providing an information interface comprising annotated timeslots.

FIG. 6B is an illustration of an example of expanding a condensed eventsummary of an information interface.

FIG. 7 is an illustration of an example of providing an informationinterface as a year-in-review interface.

FIG. 8 is an illustration of an example of providing an informationinterface as a timeline.

FIG. 9 is an illustration of an exemplary computer readable mediumwherein processor-executable instructions configured to embody one ormore of the provisions set forth herein may be comprised.

FIG. 10 illustrates an exemplary computing environment wherein one ormore of the provisions set forth herein may be implemented.

DETAILED DESCRIPTION

The claimed subject matter is now described with reference to thedrawings, wherein like reference numerals are generally used to refer tolike elements throughout. In the following description, for purposes ofexplanation, numerous specific details are set forth in order to providean understanding of the claimed subject matter. It may be evident,however, that the claimed subject matter may be practiced without thesespecific details. In other instances, structures and devices areillustrated in block diagram form in order to facilitate describing theclaimed subject matter.

An embodiment of populating an information interface based upon socialmedia data is illustrated by an exemplary method 100 of FIG. 1. At 102,the method starts. At 104, social media data may be obtained from one ormore social media sources. In an example, social network posts may beextracted from a social network, microblog messages may be extractedfrom a microblog discussion network, search queries may be extractedfrom a search engine network, hashtags may be extracted from a firstsocial media source, images may be extracted from an image sharingnetwork, a link may be extracted from a second social media source,multimedia content may be extracted from a third social media source,etc. In another example, a social media source may provide a ranked listof social media data maintained by the social media source (e.g.,hashtags, images, posts, or other social media entries having relativelyhigh popularity rankings based upon an amount of shares, likes, views,occurrences, etc.). In this way, the social media data may be extractedfrom various social media sources. Because the social media data maycomprise redundant data (e.g., hundreds of instances of a soccer gamewinning shot photo), deduplication may be performed on the social mediadata.

The social media data may be grouped into sets of social media databased upon time ranges (e.g., days, weeks, months, etc.). Accordingly, afirst set of social media is identified from the social media data, at106. The first set of social media data may correspond to a first timerange (e.g., social media entries corresponding to a particular day). Inthis way, the social media data may be grouped based upon temporalcriteria, such as days of the year.

Respective sets of social media data may be clustered by topics intotopic clusters (e.g., the first set of social media data may have socialmedia entries corresponding to a soccer game topic, a business mergertopic, and a new amusement park topic for the first time range; a secondset of social media data may have social media entries corresponding toa plane crash topic, a baseball game topic, and a new movie releasetopic for a second time range). Accordingly, a first topic cluster isidentified from the first set of social media data, at 108. The firsttopic cluster comprises a first social media entry and/or other socialmedia entries having topic similarities above a first topic clusteringthreshold (e.g., social media entries corresponding to a soccer game maybe clustered into a soccer game topic cluster). In an example, a secondtopic cluster is identified from the second set of social media data.The second topic cluster comprises a second social media entry and/orother social media entries having topic similarities above a secondtopic clustering threshold (e.g., social media entries corresponding toa plane crash may be clustered into a plane crash topic cluster). Inthis way, social media entries within respective sets of social mediadata may be clustered into topic clusters.

In an example, one or more entities may be identified from social mediaentries within a topic cluster. For example, a first entity (e.g., asoccer player A who plays for Team A) may be identified from a firstsocial media entry. A second entity (e.g., soccer player B who plays forTeam B) may be identified from a second social media entry. Arelationship between the first entity and the second entity may bedetermined (e.g., Team A played Team B in the soccer game where player Ascored a winning shot past player B). In this way, the first socialmedia entry and the second social media entry may be included within thefirst topic cluster based upon the relationship. The relationship may beused for deduplication, clustering, event summary generation, etc.

Event summaries may be generated for respective topic clusters.Accordingly, a first event summary may be generated for the first timerange based upon the first topic cluster, at 110. The first eventsummary may comprise various descriptive information associated withevents and/or entities of the first topic cluster. For example, an eventdescription (e.g., a caption derived from text of social media entrieswithin the soccer game topic cluster having relatively high rankingscorresponding to quality, relevancy, popularity, etc.) of the soccergame, an image of a game winning shot (e.g., an image having a thresholdnumber of shares, likes, views, etc.), an entity description of a soccerplayer (e.g., identified from text of social media entries within thesoccer game topic cluster), a category (e.g., a sports category assignedto the first topic cluster), a hashtag (e.g., a hashtag#championshipwinners used to tag a threshold number of social mediaentries), a link to web content (e.g., a team roster), a link to asocial network page (e.g., a team A social network profile), and/or avariety of other information may be used to generate and/or be comprisedwithin the first event summary. A second event summary may be generatedfor the first time range based upon the second topic cluster (e.g.,information relating to or identifying the plane crash).

Timeslots (e.g., representing days, weeks, months, etc.) of aninformation interface, such as a calendar, a carousel, a timeline, orother interface, may be populated with event summaries to createannotated timeslots for the information interface. Accordingly, a firsttimeslot, associated with the first time range, may be populated withthe first event summary to create a first annotated timeslot, at 112. Inan example, the first annotated timeslot may be annotated with the firstevent summary and/or the second event summary. In this way, the firsttimeslot may be annotated with event summaries corresponding to thefirst time range (e.g., event summaries for a particular day representedby the first annotated timeslot). In an example, an event summary, usedto populate a timeslot, may correspond to a recurring event, such as theOlympics. Accordingly, a future timeslot of the information interfacemay be populated with a future occurrence of the recurring event.

In an example, a plurality of timeslots of the information interface maybe populated with event summaries to create a plurality of annotatedtimeslots. For example, a second set of social media data may beidentified from the social media data. The second set of social mediadata may correspond to a second time range (e.g., the first time rangemay correspond to Sep. 12, 2013 and the second time range may correspondto Sep. 13, 2013). A second topic cluster may be identified from thesecond set of social media data. The second topic cluster may comprise asecond social media entry and/or other social media entries having topicsimilarity above a second topic clustering threshold. A second eventsummary may be generated for the second time range based upon the secondtopic cluster. A second timeslot, associated with the second time range,of the information interface may be populated with the second eventsummary to create a second annotated timeslot.

The information interface may be provided according to a variety ofinterface types. In an example, the information interface may beprovided as a calendar (e.g., a day of the calendar may correspond to anannotated timeslot such that the day may be annotated with one or moreevent summaries or condensed event summaries that are populated withinthe annotated timeslot). For example, a calendar may be augmented usingthe information interface to create an augmented calendar. The calendarmay be provided as a carousel interface, a calendar application,embedded within a search results page, provided through an operatingsystem search interface such as a search charm, and/or any other type ofuser interface. In an example, the information interface may be filteredbased upon various filter criteria, or rather various filter criteriamay be applied to the information interface such that the informationinterface is merely populated with corresponding, relevant, etc.information. For example, a user may filter the information interfacebased upon interests of the user (e.g., a particular genre of videogames), entity types (e.g., people, places, organizations, etc.), and/orcategories (e.g., politics, sports, world, movies, etc.), etc. Thefilter criteria may be specified by the user or may be provided to theuser for selection, for example.

In another example, the information interface may be provided as atimeline (e.g., a day of the timeline may correspond to an annotatedtimeslot such that the day may be annotated with one or more eventsummaries or condensed event summaries that are populated within theannotated timeslot). The timeline may comprise an interactive timelinethat may facilitate user navigation amongst one or more annotatedtimeslots (e.g., a zoom-in navigation to display annotated timeslots ata higher granularity over a shorter timespan; a zoom-out navigation todisplay annotated timeslots at a lower granularity over a largertimespan; a scroll navigation to view annotated timeslots correspondingto a new timespan; etc.). In another example, the information interfacemay be provided as a carousel interface comprising a plurality ofcarousel panes where a carousel pane corresponds to an annotatedtimeslot (e.g., one or more event summaries or condensed event summariesof an annotated timeslot may be used to annotate a correspondingcarousel pane). In another example, the information interface may beprovided as a year-in-review interface comprising annotated timeslotscorresponding to days of a year.

In an example, the information interface may be populated based upon aprofile of a user. For example, the profile of the user (e.g., a profilebased upon a social network profile, email messages sent/received by theuser, topics discussed by the user such as through a microblog session,etc.) may be evaluated to identify a first interest of the user. One ormore event summaries may be selectively displayed through theinformation interface based upon the one or more event summariescorresponding to the first interest. For example, the user may have aninterest in soccer but may have expressed a disinterest in politics.Accordingly, soccer event summaries, but not political event summaries,may be populated within the information interface. In an example, theinformation interface may be populated with a plurality of eventsummaries. A first set of event summaries, but not a second set of eventsummaries, may be selectively displayed based upon a filter criteria(e.g., the user may select a videogame filter criteria such that merelyvideogame event summaries are displayed). In an example, the informationinterface may be provided as an interactive interface. A first set ofannotated timeslots may be displayed through the interactive interfacebased upon a first view granularity. The first set of annotatedtimeslots may correspond to a first event summary granularity (e.g.,event summaries populated at a monthly granularity). Responsive to azoom input associated with the interactive interface, display of thefirst set of annotated timeslots may be transitioned to a second set ofannotated timeslots based upon a second view granularity specified bythe zoom input. The second set of annotated timeslots may correspond toa second event summary granularity (e.g., event summaries populated at aweekly granularity) different than the first event summary granularity.In this way, event summaries may be derived from social media data, andmay be used to populate an information interface such as a calendar,carousel, timeline, and/or other (e.g., interactive) interface. At 114,the method ends.

FIG. 2 illustrates an example of a system 200 for obtaining social mediadata. The system 200 comprises an information interface populationcomponent 202. The information interface population component 202 isconfigured to obtain social media data from one or more social mediasources, which may be used to populate an information interface withevent summaries derived from the social media data, for example. Theinformation interface population component 202 may obtain school socialnetwork posts 206 from a school social network 204, shared articles 212from a professional social network 210, images 216 from an image sharingnetwork 214, discussion data 220 from a microblog network 218, personalsocial network posts 224 from a personal social network 222, searchquery activity 228 from a search engine network 226, and/or other socialmedia data from other social media sources.

FIG. 3 illustrates an example of a system 300 for identifying sets ofsocial media data. The system 300 comprises an information interfacepopulation component 202. In an example, the information interfacepopulation component 202 may have obtained social media data fromvarious social media sources (e.g., FIG. 2). The information interfacepopulation component 202 may be configured to identify a first set ofsocial media data 304, a second set of social media data 306, a thirdset of social media data 308, and/or other sets of social media datafrom the social media data based upon temporal criteria. In an example,the sets of social media data are identified based upon time ranges,such as days of the year. For example, the first set of social mediadata 304 comprises one or more social media entries corresponding toJul. 4, 2013 (e.g., social media entries pertaining to a Clevelandparade, a Tampa fighter jet show, a soccer game, and/or other eventsoccurring on Jul. 4, 2013), the second set of social media data 306comprises one or more social media entries corresponding to Jul. 5, 2013(e.g., social media entries pertaining to a Netherlands earthquake, acompany merger, and/or other events occurring on Jul. 5, 2013), and thethird set of social media data 308 comprises one or more social mediaentries corresponding to Jul. 6, 2013 (e.g., social media entriespertaining to an increase in the stock market, Olympic trials, and/orother events occurring on Jul. 6, 2013).

FIG. 4 illustrates an example of a system 400 for identifying topicclusters for sets of social media data. The system 400 comprises aninformation interface population component 202. In an example, theinformation interface population component 202 may have identified setsof social media data, such as a first set of social media data 304corresponding to social media entries occurring on Jul. 4, 2013 (e.g.,FIG. 3). The information interface population component 202 may beconfigured to cluster social media entries within the first set ofsocial media data 304 based upon topics similarity. In an example, theinformation interface population component 202 may identify a firsttopic cluster 402 based upon one or more social media entries havingsimilar features (e.g., textual features, imagery features, etc.). Forexample, a “picture of our family at the Cleveland parade” socialnetwork post, a Cleveland parade is a hit news article shared through asocial network, a fire truck at CLE parade image shared through an imagesharing network, and/or other social media entries corresponding to aCleveland parade topic above a first topic similarity may be identifiedas the first topic cluster 402. In another example, a fighter jet imageshared through a social network using a hashtag #tampafighterjetshow, a“did anyone else see the fighter show in Tampa” social network post, asearch query Tampa Bay jet show, and/or other social media entriescorresponding to a fighter jet show topic above a second topicsimilarity threshold may be identified as a second topic cluster 404. Inanother example, a “soccer sports championship with player A” microblogdiscussion message, a “great soccer game seeing player B” social networkpost, a picture of player A from Team A shared through a social network,a picture of player B from Team B shared through an image sharingnetwork, an article on championship game between Team A and Team Bposted by a sports network, and/or other social media entriescorresponding to a soccer championship topic above a third topicsimilarity may be identified as a third topic cluster 406.

Because a topic cluster may comprise redundant social media entries(e.g., the first topic cluster may comprise 2,000 instances of the firetruck at CLE parade image), the information interface populationcomponent 202 may be configured to remove duplicate social media entriesutilizing deduplication functionality. In an example, the informationinterface population component 202 may be configured to rank socialmedia entries based upon various ranking criteria, such as a number ofshares, a number of likes, a number of views, quality, relevancy, userinterest, user interaction, and/or other ranking criteria.

The information interface population component 202 may be configured togenerate event summaries for respective topics clusters. For example, afirst event summary may be created for the first topic cluster 402. Thefirst event summary may comprise information related to a Clevelandparade event (e.g., hashtags used to discuss the Cleveland parade event,an image of the Cleveland parade event, and/or a variety of otherinformation about the Cleveland parade event). A second event summarymay be created for the second topic cluster 404. The second eventsummary may comprise information related to a Tampa Bay fighter jet showevent (e.g., hashtags used to discuss the Tampa Bay fighter jet showevent, information about a fighter pilot entity, a description of theTampa Bay fighter jet show event, an image from the Tampa Bay fighterjet show event, a link to a fighter jet social network profile, etc.).In this way, event summaries may be created for topic clusters. Theevent summaries may be used to populate timeslots of an informationinterface to create annotated timeslots (e.g., FIGS. 6A-8).

FIG. 5 illustrates an example of a system 500 for identifying arelationship between entities associated with social media entries. Thesystem 500 comprises an information interface population component 202.In an example, the information interface population component 202 mayhave identified a third topic cluster 406 based upon one or more socialmedia entries having topic similarities above a third topic clusteringthreshold (e.g., FIG. 4). The information interface population component202 may be configured to identify a first entity associated with a firstsocial media entry. For example, the information interface populationcomponent 202 may identify a player A who plays for Team A based uponone or more social media entries within the third topic cluster 406,such as a “soccer sports championship with player A” microblogdiscussion message, a picture of player A from Team A scoring a winninggoal shared through a social network, and/or an article on championshipgame between Team A and Team B posted by a sports network. Theinformation interface population component 202 may be configured toidentify a second entity associated with a second social media entry.For example, the information interface population component 202 mayidentify a player B of Team B from one or more social media entrieswithin the third topic cluster 406, such as a “great soccer game seeingplayer B” social network post, a picture of player B from Team B being agoalie shared through an image sharing network, and/or the article onchampionship game between Team A and Team B.

The information interface population component 202 may determine that arelationship 502 exists between the player A of Team A and the player Bof Team B. For example, the relationship 502 may specify that Team Aplayed Team B in a championship soccer match where player A from Team Ascored a winning goal past player B of Team B. The relationship 502 maybe used for clustering (e.g., a determination as to whether one or moresocial media entries are to be or remain clustered within the thirdtopic cluster 406), event summary generation (e.g., a soccerchampionship event summary may be derived from information within therelationship 502), categorization of topic clusters (e.g., theassignment of a sports category and/or the soccer championship topic tothe third topic cluster 406), etc.

FIG. 6A illustrates an example of a system 600 for providing aninformation interface 604 comprising annotated timeslots. The system 600comprises an information interface population component 202. In anexample, the information interface population component 202 may haveidentified one or more topic clusters of social media entries (e.g.,FIG. 4). The information interface population component 202 may havegenerated one or more event summaries for time ranges based upon topicclusters. For example, a second topic cluster 404 of a first set ofsocial media data 304 may be used to generate a Tampa Bay fighter jetshow event summary (e.g., corresponding to a condensed first eventsummary 618) for a first time range of Jul. 4, 2013 (e.g., correspondingto a first annotated timeslot 606 of the information interface 604). TheTampa Bay fighter jet show event summary may comprise informationrelated to a Tampa fighter jet show derived from social media data. Athird topic cluster 406 of the first set of social media data 304 may beused to generate a soccer championship event summary (e.g.,corresponding to a condensed second event summary 620) for the firsttime range of Jul. 4, 2013 (e.g., corresponding to the first annotatedtimeslot 606 of the information interface 604). The soccer championshipevent summary may comprise information related to a soccer championshipgame derived from social media data. An oil company merger topic clusterof a second set of social media data 306 may be used to generate an oilcompany merger event summary (e.g., corresponding to a condensed thirdevent summary 622) for a second time range of Jul. 15, 2013 (e.g.,corresponding to a second annotated timeslot 608 of the informationinterface 604). The oil company merger event summary may compriseinformation related to an oil company merger derived from social mediadata. In this way, event summaries may be generated and used to populatetimeslots of the information interface 604 as annotated timeslots.

In an example, the information interface 604 comprises an augmentedcalendar comprising annotated timeslots, such as the first annotatedtimeslot 606 populated with the condensed first event summary 618 andthe condensed second event summary 620, the second annotated timeslot608 populated with the condensed third event summary 622 and a condensedfourth event summary for a plane crash event, and/or a third annotatedtimeslot 610 (e.g., corresponding to a third time range of Jul. 16,2013) populated with a condensed fifth event summary for a stock marketsurge event and a condensed sixth event summary for a new military jetsdeployed event. A user may navigate between various time ranges of theinformation interface 604. For example, responsive to a view olderinput, annotated timeslots corresponding to time ranges before July14^(th) may be displayed. Responsive to a view newer input, annotatedtimeslots corresponding to time ranges after July 16^(th) may bedisplayed. Responsive to receiving a search query through a searchinterface 616, one or more annotated timeslots populated with eventsummaries corresponding to the search query may be displayed.

In an example, the information interface population component 202 may beconfigured to evaluate a user profile 602 of a user to identify one ormore interests of the user, such as a fighter jet interest (e.g., basedupon a social network profile of the user), a soccer interest (e.g.,based upon microblog messages of the user having #soccer tags), and astock market interest (e.g., based upon emails of the user regarding thestock market). The information interface population component 202 may beconfigured to selectively display one or more event summaries throughthe information interface 604 based upon the one or more event summariescorresponding to the one or more interests of the user. For example, theinformation interface population component 202 may display the condensedfirst event summary 618, corresponding to the fighter jet interest, andthe condensed second event summary 620, corresponding to the soccerinterest, but not a condensed event summary corresponding to aNetherlands earthquake that may be populated within the first annotatedtimeslot 606. In an example, the information interface 604 may befiltered by date 612 (e.g., the user may specify a date range of Apr. 4,2012 to Jun. 4, 2012 such that the information interface 604 ispopulated with annotated timeslots between Apr. 4, 2012 and Jun. 4,2012), filtered by category 614 (e.g., the user may specify a sportscategory such that the information interface is selectively populatedwith event summaries corresponding to sports), etc.

FIG. 6B illustrates an example 650 of expanding a condensed eventsummary of an information interface 604. In an example, the informationinterface 604 corresponds to the information interface 604 of FIG. 6A.The information interface 604 comprises one or more annotated timeslots,such as a first annotated timeslot 606 populated with a second condensedevent summary 618 and/or other condensed event summaries, a secondannotated timeslot 608 populated with one or more condensed eventsummaries, and/or a third annotated timeslot 610 populated with one ormore condensed event summaries.

In an example, the second condensed event summary 618 is selected.Responsive to the selection, a soccer championship game event summary652 is displayed. The soccer championship game event summary 652comprises various information about a soccer championship game event.For example, the soccer championship game event summary 652 specifies alink to a Team A victory article, a soccer ball image captured duringthe soccer championship game event and tagged with a hashtag#winningball, a link to a player A winning goal video, a link to aplayer A social network profile, etc.

FIG. 7 illustrates an example 700 of providing an information interfaceas a year-in-review interface 726. The year-in-review interface 726 maycomprise timeslots corresponding to months of the year 2013. Thetimeslots may be populated with event summaries, derived from socialmedia data, to create annotated timeslots. For example, a firstannotated timeslot 702 for January 2013 is populated with a Japan snowblizzard event summary and/or summaries of other events that occurred inJanuary, a second annotated timeslot 704 for February 2013 is populatedwith a football championship event summary and/or summaries of otherevents that occurred in February, a third annotated timeslot 706 forMarch 2013 is populated with a peace treaty event summary and/orsummaries of other events that occurred March, and/or other annotatedtimeslots are populated with event summaries derived from social mediadata. It may be appreciated that the year-in-review interface 726 maydisplay event summaries at various granularity (e.g., a weekgranularity, a day granularity, etc.). In this way, a user may beprovided with a snapshot of main events that may have been popular(e.g., shared by a large number of social network users above a sharingthreshold), significant (e.g., viewed by a large number of socialnetwork users above a viewing threshold), trending (e.g., discussed by alarge number of social network users in a relatively short period oftime above a trending threshold), etc. The information interface may betailored to interests of the user, such that the user is presented withevent summaries that are of interest to the user (e.g., sports related)but is not presented with event summaries that are not of interest tothe user (e.g., political).

FIG. 8 illustrates an example 800 of providing an information interfaceas a timeline 802. The timeline 802 may comprise a plurality ofannotated timeslots. In an example, the timeline 802 may displayannotated timeslots at a monthly granularity between June 2013 andSeptember 2013. A zoom-in interface element 806 and/or a zoom-outinterface element 808 may be used to zoom into particular viewgranularities (e.g., a daily granularity, a year-in-review granularity,etc.). A select date range interface element 810 may be used to displayannotated timeslots within a particular date range, such as June 2013 toSeptember 2013. A sort interface element 812 may be used to filter eventsummaries, populated within the annotated timeslots, by category such asa gaming category. In an example, an August 2013 annotated timeslot 804may be selected. Responsive to the selection, a set of event summaries814, populated within the August 2013 annotated timeslot 804, may bedisplayed. The set of event summaries 814 may correspond to the gamingcategory selected through the sort interface element 812. For example, avideo gaming convention event summary, a new video game console detailsreveal event summary, a violent videogame doesn't get rating inAustralia event summary, and a link to new video game trailer eventsummary may be displayed. In this way, a user may view various eventsummaries, derived from social media data, through the timeline 802.

Still another embodiment involves a computer-readable medium comprisingprocessor-executable instructions configured to implement one or more ofthe techniques presented herein. An example embodiment of acomputer-readable medium or a computer-readable device is illustrated inFIG. 9, wherein the implementation 900 comprises a computer-readablemedium 908, such as a CD-R, DVD-R, flash drive, a platter of a hard diskdrive, etc., on which is encoded computer-readable data 906. Thiscomputer-readable data 906, such as binary data comprising at least oneof a zero or a one, in turn comprises a set of computer instructions 904configured to operate according to one or more of the principles setforth herein. In some embodiments, the processor-executable computerinstructions 904 are configured to perform a method 902, such as atleast some of the exemplary method 100 of FIG. 1, for example. In someembodiments, the processor-executable instructions 904 are configured toimplement a system, such as at least some of the exemplary system 200 ofFIG. 2, at least some of the exemplary system 300 of FIG. 3, at leastsome of the exemplary system 400 of FIG. 4, at least some of the system500 of FIG. 5, and/or at least some of the exemplary system 600 of FIG.6A, for example. Many such computer-readable media are devised by thoseof ordinary skill in the art that are configured to operate inaccordance with the techniques presented herein.

Although the subject matter has been described in language specific tostructural features and/or methodological acts, it is to be understoodthat the subject matter defined in the appended claims is notnecessarily limited to the specific features or acts described above.Rather, the specific features and acts described above are disclosed asexample forms of implementing at least some of the claims.

As used in this application, the terms “component,” “module,” “system”,“interface”, and/or the like are generally intended to refer to acomputer-related entity, either hardware, a combination of hardware andsoftware, software, or software in execution. For example, a componentmay be, but is not limited to being, a process running on a processor, aprocessor, an object, an executable, a thread of execution, a program,and/or a computer. By way of illustration, both an application runningon a controller and the controller can be a component. One or morecomponents may reside within a process and/or thread of execution and acomponent may be localized on one computer and/or distributed betweentwo or more computers.

Furthermore, the claimed subject matter may be implemented as a method,apparatus, or article of manufacture using standard programming and/orengineering techniques to produce software, firmware, hardware, or anycombination thereof to control a computer to implement the disclosedsubject matter. The term “article of manufacture” as used herein isintended to encompass a computer program accessible from anycomputer-readable device, carrier, or media. Of course, manymodifications may be made to this configuration without departing fromthe scope or spirit of the claimed subject matter.

FIG. 10 and the following discussion provide a brief, generaldescription of a suitable computing environment to implement embodimentsof one or more of the provisions set forth herein. The operatingenvironment of FIG. 10 is only one example of a suitable operatingenvironment and is not intended to suggest any limitation as to thescope of use or functionality of the operating environment. Examplecomputing devices include, but are not limited to, personal computers,server computers, hand-held or laptop devices, mobile devices (such asmobile phones, Personal Digital Assistants (PDAs), media players, andthe like), multiprocessor systems, consumer electronics, mini computers,mainframe computers, distributed computing environments that include anyof the above systems or devices, and the like.

Although not required, embodiments are described in the general contextof “computer readable instructions” being executed by one or morecomputing devices. Computer readable instructions may be distributed viacomputer readable media (discussed below). Computer readableinstructions may be implemented as program modules, such as functions,objects, Application Programming Interfaces (APIs), data structures, andthe like, that perform particular tasks or implement particular abstractdata types. Typically, the functionality of the computer readableinstructions may be combined or distributed as desired in variousenvironments.

FIG. 10 illustrates an example of a system 1000 comprising a computingdevice 1012 configured to implement one or more embodiments providedherein. In one configuration, computing device 1012 includes at leastone processing unit 1016 and memory 1017. Depending on the exactconfiguration and type of computing device, memory 1017 may be volatile(such as RAM, for example), non-volatile (such as ROM, flash memory,etc., for example) or some combination of the two. This configuration isillustrated in FIG. 10 by dashed line 1014.

In other embodiments, device 1012 may include additional features and/orfunctionality. For example, device 1012 may also include additionalstorage (e.g., removable and/or non-removable) including, but notlimited to, magnetic storage, optical storage, and the like. Suchadditional storage is illustrated in FIG. 10 by storage 1020. In oneembodiment, computer readable instructions to implement one or moreembodiments provided herein may be in storage 1020. Storage 1020 mayalso store other computer readable instructions to implement anoperating system, an application program, and the like. Computerreadable instructions may be loaded in memory 1017 for execution byprocessing unit 1016, for example.

The term “computer readable media” as used herein includes computerstorage media. Computer storage media includes volatile and nonvolatile,removable and non-removable media implemented in any method ortechnology for storage of information such as computer readableinstructions or other data. Memory 1017 and storage 1020 are examples ofcomputer storage media. Computer storage media includes, but is notlimited to, RAM, ROM, EEPROM, flash memory or other memory technology,CD-ROM, Digital Versatile Disks (DVDs) or other optical storage,magnetic cassettes, magnetic tape, magnetic disk storage or othermagnetic storage devices, or any other medium which can be used to storethe desired information and which can be accessed by device 1012. Anysuch computer storage media may be part of device 1012.

Device 1012 may also include communication connection(s) 1026 thatallows device 1012 to communicate with other devices. Communicationconnection(s) 1026 may include, but is not limited to, a modem, aNetwork Interface Card (NIC), an integrated network interface, a radiofrequency transmitter/receiver, an infrared port, a USB connection, orother interfaces for connecting computing device 1012 to other computingdevices. Communication connection(s) 1026 may include a wired connectionor a wireless connection. Communication connection(s) 1026 may transmitand/or receive communication media.

The term “computer readable media” may include communication media.Communication media typically embodies computer readable instructions orother data in a “modulated data signal” such as a carrier wave or othertransport mechanism and includes any information delivery media. Theterm “modulated data signal” may include a signal that has one or moreof its characteristics set or changed in such a manner as to encodeinformation in the signal.

Device 1012 may include input device(s) 1024 such as keyboard, mouse,pen, voice input device, touch input device, infrared cameras, videoinput devices, and/or any other input device. Output device(s) 1022 suchas one or more displays, speakers, printers, and/or any other outputdevice may also be included in device 1012. Input device(s) 1024 andoutput device(s) 1022 may be connected to device 1012 via a wiredconnection, wireless connection, or any combination thereof. In oneembodiment, an input device or an output device from another computingdevice may be used as input device(s) 1024 or output device(s) 1022 forcomputing device 1012.

Components of computing device 1012 may be connected by variousinterconnects, such as a bus. Such interconnects may include aPeripheral Component Interconnect (PCI), such as PCI Express, aUniversal Serial Bus (USB), firewire (IEEE 1394), an optical busstructure, and the like. In another embodiment, components of computingdevice 1012 may be interconnected by a network. For example, memory 1017may be comprised of multiple physical memory units located in differentphysical locations interconnected by a network.

Those skilled in the art will realize that storage devices utilized tostore computer readable instructions may be distributed across anetwork. For example, a computing device 1030 accessible via a network1027 may store computer readable instructions to implement one or moreembodiments provided herein. Computing device 1012 may access computingdevice 1030 and download a part or all of the computer readableinstructions for execution. Alternatively, computing device 1012 maydownload pieces of the computer readable instructions, as needed, orsome instructions may be executed at computing device 1012 and some atcomputing device 1030.

Various operations of embodiments are provided herein. In oneembodiment, one or more of the operations described may constitutecomputer readable instructions stored on one or more computer readablemedia, which if executed by a computing device, will cause the computingdevice to perform the operations described. The order in which some orall of the operations are described should not be construed as to implythat these operations are necessarily order dependent. Alternativeordering will be appreciated by one skilled in the art having thebenefit of this description. Further, it will be understood that not alloperations are necessarily present in each embodiment provided herein.Also, it will be understood that not all operations are necessary insome embodiments.

Further, unless specified otherwise, “first,” “second,” and/or the likeare not intended to imply a temporal aspect, a spatial aspect, anordering, etc. Rather, such terms are merely used as identifiers, names,etc. for features, elements, items, etc. For example, a first object anda second object generally correspond to object A and object B or twodifferent or two identical objects or the same object.

Moreover, “exemplary” is used herein to mean serving as an example,instance, illustration, etc., and not necessarily as advantageous. Asused herein, “or” is intended to mean an inclusive “or” rather than anexclusive “or”. In addition, “a” and “an” as used in this applicationare generally be construed to mean “one or more” unless specifiedotherwise or clear from context to be directed to a singular form. Also,at least one of A and B and/or the like generally means A or B or both Aand B. Furthermore, to the extent that “includes”, “having”, “has”,“with”, and/or variants thereof are used in either the detaileddescription or the claims, such terms are intended to be inclusive in amanner similar to the term “comprising”.

Also, although the disclosure has been shown and described with respectto one or more implementations, equivalent alterations and modificationswill occur to others skilled in the art based upon a reading andunderstanding of this specification and the annexed drawings. Thedisclosure includes all such modifications and alterations and islimited only by the scope of the following claims. In particular regardto the various functions performed by the above described components(e.g., elements, resources, etc.), the terms used to describe suchcomponents are intended to correspond, unless otherwise indicated, toany component which performs the specified function of the describedcomponent (e.g., that is functionally equivalent), even though notstructurally equivalent to the disclosed structure. In addition, while aparticular feature of the disclosure may have been disclosed withrespect to only one of several implementations, such feature may becombined with one or more other features of the other implementations asmay be desired and advantageous for any given or particular application.

1-20. (canceled)
 21. A computing device comprising: one or moreprocessing units; and one or more computer-readable media comprisingcomputer-executable instructions, which, when executed by the one ormore processing units, cause the computing device to: obtain socialmedia data from multiple disparate social media sources; identify afirst set of social media data from the social media data, the first setof social media data comprising only social media data that correspondto a first time range; identify a first topic cluster from theidentified first set of social media data, the first topic clustercomprising a first set of multiple, different social media entries, eachof which has a topic similarity above a first topic clusteringthreshold; generate a first event summary for the first time range basedupon the first topic cluster, the first event summary comprising textthat is indicative of events or entities of the first topic cluster;generate an information interface comprising multiple annotatedtimeslots, including a first annotated timeslot that comprises the firstevent summary; and transmit the information interface to a secondcomputing device that is separate from the computing device and iscommunicationally coupled to the computing device through a computernetwork; wherein the second computing device visually generates, on ahardware display device communicationally coupled thereto, theinformation interface, including the first annotated timeslot and thefirst event summary.
 22. The computing device of claim 21, wherein theannotated timeslots each have a duration of a day, a week or a month;and wherein further the information interface is in a calendar format.23. The computing device of claim 21, wherein the one or morecomputer-readable media comprise further computer-executableinstructions, which, when executed by the one or more processing unitscause the computing device to: identify a second topic cluster from thefirst set of social media data, the second topic cluster comprising asecond set of multiple, different social media entries, each of whichhas a topic similarity above a second topic clustering threshold; andgenerate a second event summary for the first time range based upon thesecond topic cluster, the second event summary comprising text that isindicative of events or entities of the second topic cluster; whereinthe first annotated timeslot of the information interface furthercomprises the second event summary.
 24. The computing device of claim21, wherein the one or more computer-readable media comprise furthercomputer-executable instructions, which, when executed by the one ormore processing units cause the computing device to: identify a secondset of social media data from the social media data, the second set ofsocial media data comprising only social media data that correspond to asecond time range that is different from, and exclusive of, the firsttime range; identify a second topic cluster from the identified secondset of social media data, the second topic cluster comprising a secondset of multiple, different social media entries, each of which has atopic similarity above a second topic clustering threshold; and generatea second event summary for the second time range based upon the secondtopic cluster, the second event summary comprising text that isindicative of events or entities of the second topic cluster; whereinthe multiple annotated timeslots of the information interface furthercomprise a second annotated timeslot that comprises the second eventsummary.
 25. The computing device of claim 21, wherein the multipleannotated timeslots correspond to a first event summary granularity; andwherein further the one or more computer-readable media comprise furthercomputer-executable instructions, which, when executed by the one ormore processing units cause the computing device to: generate asubsequent information interface comprising multiple annotated timeslotscorresponding to a second event summary granularity, differing from thefirst event summary granularity; wherein the second event summarygranularity was specified by a zoom input that was received by thesecond computing device.
 26. The computing device of claim 21, whereinthe one or more computer-readable media comprise furthercomputer-executable instructions, which, when executed by the one ormore processing units cause the computing device to: performdeduplication on the obtained social media data.
 27. The computingdevice of claim 21, wherein the computer-executable instructions, which,when executed by the one or more processing units, cause the computingdevice to identify the first topic cluster, comprise computer-executableinstructions, which, when executed by the one or more processing unitscause the computing device to: identify a first entity associated with afirst social media entry from the first set of social media data;identify a second entity associated with a second social media entryfrom the first set of social media data; determine that a relationshipexists between the first entity and the second entity; and include,based on the determined relationship, both the first and the secondsocial media entries in the first topic cluster as part of the multiple,different social media entries of which the first topic cluster iscomprised.
 28. The computing device of claim 21, wherein the one or morecomputer-readable media comprise further computer-executableinstructions, which, when executed by the one or more processing unitscause the computing device to: determine that the first event summarycorresponds to a recurring event; and update the information interfaceto include a future annotated timeslot indicating a future occurrence ofthe recurring event.
 29. The computing device of claim 21, wherein theone or more computer-readable media comprise further computer-executableinstructions, which, when executed by the one or more processing unitscause the computing device to: evaluate a profile of a user to identifyinterests of the user; wherein the information interface comprises thefirst annotated timeslot only if the first event summary corresponds tothe identified interests of the user.
 30. A method of improvingprovision of social media data to a user by generating an informationinterface that will be presented to a user by being visually generatedon a hardware display device, the method comprising: obtaining, at a setof one or more computing devices, social media data from multipledisparate social media sources; identifying, at the set of one or morecomputing devices, a first set of social media data from the socialmedia data, the first set of social media data comprising only socialmedia data that correspond to a first time range; identifying, at theset of one or more computing devices, a first topic cluster from theidentified first set of social media data, the first topic clustercomprising a first set of multiple, different social media entries, eachof which has a topic similarity above a first topic clusteringthreshold; generating, at the set of one or more computing devices, afirst event summary for the first time range based upon the first topiccluster, the first event summary comprising text that is indicative ofevents or entities of the first topic cluster; generating, at the set ofone or more computing devices, the information interface comprisingmultiple annotated timeslots, including a first annotated timeslot thatcomprises the first event summary; and transmitting, from one of the setof one or more computing devices, the information interface to a secondcomputing device that is separate from the set of one or more computingdevices and is communicationally coupled to at least some of the set ofone or more computing devices through a computer network; wherein thesecond computing device visually generates, on a hardware display devicecommunicationally coupled thereto, the information interface, includingthe first annotated timeslot and the first event summary.
 31. The methodof claim 30, further comprising: identifying, at the set of one or morecomputing devices, a second topic cluster from the first set of socialmedia data, the second topic cluster comprising a second set ofmultiple, different social media entries, each of which has a topicsimilarity above a second topic clustering threshold; and generating, atthe set of one or more computing devices, a second event summary for thefirst time range based upon the second topic cluster, the second eventsummary comprising text that is indicative of events or entities of thesecond topic cluster; wherein the first annotated timeslot of theinformation interface further comprises the second event summary. 32.The method of claim 30, further comprising: identifying, at the set ofone or more computing devices, a second set of social media data fromthe social media data, the second set of social media data comprisingonly social media data that correspond to a second time range that isdifferent from, and exclusive of, the first time range; identifying, atthe set of one or more computing devices, a second topic cluster fromthe identified second set of social media data, the second topic clustercomprising a second set of multiple, different social media entries,each of which has a topic similarity above a second topic clusteringthreshold; and generating, at the set of one or more computing devices,a second event summary for the second time range based upon the secondtopic cluster, the second event summary comprising text that isindicative of events or entities of the second topic cluster; whereinthe multiple annotated timeslots of the information interface furthercomprise a second annotated timeslot that comprises the second eventsummary.
 33. The method of claim 30, wherein the multiple annotatedtimeslots correspond to a first event summary granularity, the methodfurther comprising: generating, at the set of one or more computingdevices, a subsequent information interface comprising multipleannotated timeslots corresponding to a second event summary granularity,differing from the first event summary granularity; wherein the secondevent summary granularity was specified by a zoom input that wasreceived by the second computing device.
 34. The method of claim 30,wherein the identifying the first topic cluster comprises: identifying,at the set of one or more computing devices, a first entity associatedwith a first social media entry from the first set of social media data;identifying, at the set of one or more computing devices, a secondentity associated with a second social media entry from the first set ofsocial media data; determining, at the set of one or more computingdevices, that a relationship exists between the first entity and thesecond entity; and including, at the set of one or more computingdevices, based on the determined relationship, both the first and thesecond social media entries in the first topic cluster as part of themultiple, different social media entries of which the first topiccluster is comprised.
 35. The method of claim 30, further comprising:determining, at the set of one or more computing devices, that the firstevent summary corresponds to a recurring event; and updating, at the setof one or more computing devices, the information interface to include afuture annotated timeslot indicating a future occurrence of therecurring event.
 36. A graphical user interface system comprising ahardware display device communicationally coupled to a computing device,the hardware display device having physically generated thereon agraphical user interface comprising: an information interface comprisingannotated timeslots, each corresponding to a defined range of time, theinformation interface being graphically presented in a calendar format;and a first annotated timeslot comprising a textual first event summarybased on a first topic cluster, identified from a first set of socialmedia data, wherein each social media entry of the first topic clusterhas a first topic similarity above a first topic clustering thresholdand each corresponds to a first time range that is associated with thefirst annotated timeslot.
 37. The graphical user interface system ofclaim 36, wherein the defined range of time is one of: a day, a week ora month.
 38. The graphical user interface system of claim 36, whereinthe first annotated timeslot comprises a textual second event summarybased on a second topic cluster, identified from the first set of socialmedia data, wherein each social media entry of the second topic clusterhas a second topic similarity above a second topic clustering thresholdand each corresponds to the first time range that is associated with thefirst annotated timeslot.
 39. The graphical user interface system ofclaim 36, further comprising: a second annotated timeslot, differingfrom the first annotated timeslot, the second annotated timeslotcomprising a textual second event summary based on a second topiccluster, identified from a second set of social media data, wherein eachsocial media entry of the second topic cluster has a second topicsimilarity above a second topic clustering threshold and eachcorresponds to a second time range that is associated with the secondannotated timeslot.
 40. The graphical user interface system of claim 36,wherein the information interface comprises a first set of annotatedtimeslots based upon a first view granularity, the first set ofannotated timeslots corresponding to a first event summary granularity;wherein, responsive to zoom input, the information interface transitionsfrom comprising the first set of annotated timeslots to comprising asecond set of annotated timeslots based upon a second view granularityspecified by the zoom input, the second set of annotated timeslotscorresponding to a second event summary granularity different than thefirst event summary granularity.